Airborne laser scanning for terrain modeling in the Amazon forest

Andrade, Mariana Silva; Görgens, Eric Bastos; Reis, Cristiano Rodrigues; Cantinho, Roberta Zecchini; Assis, Mauro; Sato, Luciane Yumie; Ometto, Jean Pierre

doi:10.1590/1809-4392201800132

Cited by 10 publications

(16 citation statements)

References 33 publications

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“…Above mentioned studies that have compared relevant filters [22][23][24][25][26][27] used different approaches to calibrating filters with custom settings, which depends strongly on the skillset of the operator. Some omitted calibration by using default settings to minimize the subjective influence of the operator [25]. However, not only are the results more accurate when filters are calibrated, but some filters are also more susceptible to calibration than others [27].…”

Section: Methods For Quantitative and Qualitative Assessmentmentioning

confidence: 99%

“…The analyzed filters are summarized in Table 2. To our knowledge PMF, SBF, SMRF, CSF, SegBF, and BMHF were not assessed in any of the previous studies [22][23][24][25][26][27].…”

Section: Evaluated Filtersmentioning

confidence: 99%

“…In the past several studies have compared relevant filters implemented in free software [22][23][24][25][26][27]. However, none of them include newer filters, none of them use a standardized comparison method by Sithole and Vosselman [20], and none of them is archaeology-specific.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Filters for Archaeology-Specific Ground Extraction from Airborne LiDAR Point Clouds

Štular

Lozić

2020

Remote Sensing

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Identifying bare-earth or ground returns within point cloud data is a crucially important process for archaeologists who use airborne LiDAR data, yet there has thus far been very little comparative assessment of the available archaeology-specific methods and their usefulness for archaeological applications. This article aims to provide an archaeology-specific comparison of filters for ground extraction from airborne LiDAR point clouds. The qualitative and quantitative comparison of the data from four archaeological sites from Austria, Slovenia, and Spain should also be relevant to other disciplines that use visualized airborne LiDAR data. We have compared nine filters implemented in free or low-cost off-the-shelf software, six of which are evaluated in this way for the first time. The results of the qualitative and quantitative comparison are not directly analogous, and no filter is outstanding compared to the others. However, the results are directly transferable to real-world problem-solving: Which filter works best for a given combination of data density, landscape type, and type of archaeological features? In general, progressive TIN (software: lasground_new) and a hybrid (software: Global Mapper) commercial filter are consistently among the best, followed by an open source slope-based one (software: Whitebox GAT). The ability of the free multiscale curvature classification filter (software: MCC-LIDAR) to remove vegetation is also commendable. Notably, our findings show that filters based on an older generation of algorithms consistently outperform newer filtering techniques. This is a reminder of the indirect path from publishing an algorithm to filter implementation in software.

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Section: Methods For Quantitative and Qualitative Assessmentmentioning

confidence: 99%

“…The analyzed filters are summarized in Table 2. To our knowledge PMF, SBF, SMRF, CSF, SegBF, and BMHF were not assessed in any of the previous studies [22][23][24][25][26][27].…”

Section: Evaluated Filtersmentioning

confidence: 99%

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Comparison of Filters for Archaeology-Specific Ground Extraction from Airborne LiDAR Point Clouds

Štular

Lozić

2020

Remote Sensing

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“…We applied an outlier filter in the original ALS clouds to remove the returns outside the range of four standard-deviation (McGaughey, 2015). The ground returns were classified by Kraus and Pfeifer (1998;2001) algorithm considering an 8-meter window size (Andrade et al, 2018) and parameters recommended by McGaughey (2015). Digital terrain models (DTM) with 1-meter resolution was created by averaging the ground points within each pixel.…”

Section: Methodsmentioning

confidence: 99%

Monitoring the understory in eucalyptus plantations using airborne laser scanning

Melo

Reis

Martins³

et al. 2021

Sci. agric. (Piracicaba, Braz.)

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In eucalyptus plantations, the presence of understory increases the risk of fires, acts as an obstacle to forest operations, and leads to yield losses due to competition. The objective of this study was to develop an approach to discriminate the presence or absence of understory in eucalyptus plantations based on airborne laser scanning surveys. The bimodal canopy height profile was modeled by two Weibull density functions: one to model the canopy, and other to model the understory. The parameters used as predictor in the logistic model successfully discriminated the presence or absence of understory. The logistic model composed by g canopy , g understory , and g understory showed higher values of accuracy (0.96) and kappa (0.92), which means an adequate classification of presence of understory and absence of understory. Weibull parameters could be used as input in the logistic regression to effectively identify the presence and absence of understory in eucalyptus plantation.

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“…The uppermost vegetation heights were then employed to compute a 1‐m horizontal resolution canopy height model (CHM). While errors in estimation of terrain height can affect CHM estimations, previous studies in tropical forests show that lidar surveys with at least 4 returns per m 2 permit accurate DTM generation and tree height estimation even in complex terrain (Andrade et al., 2018; Clark et al., 2004; Glenn et al., 2011; Leitold et al., 2015).…”

Section: Methodsmentioning

confidence: 99%

Resource availability and disturbance shape maximum tree height across the Amazon

Görgens

Nunes

Jackson

et al. 2020

Global Change Biology

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Tall trees are key drivers of ecosystem processes in tropical forest, but the controls on the distribution of the very tallest trees remain poorly understood. The recent discovery of grove of giant trees over 80 meters tall in the Amazon forest requires a reevaluation of current thinking. We used high-resolution airborne laser surveys to measure canopy height across 282,750 ha of old-growth and second-growth forests randomly sampling the entire Brazilian Amazon. We investigated how resources and disturbances shape the maximum height distribution across the Brazilian Amazon through the relations between the occurrence of giant trees and environmental factors. Common drivers of height development are fundamentally different from those influencing the occurrence of giant trees. We found that changes in wind and light availability drive giant tree distribution as much as precipitation and temperature, together shaping the forest structure of the Brazilian Amazon. The location of giant trees should be carefully considered by policymakers when identifying important hot spots for the conservation of biodiversity in the Amazon.

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Airborne laser scanning for terrain modeling in the Amazon forest

Cited by 10 publications

References 33 publications

Comparison of Filters for Archaeology-Specific Ground Extraction from Airborne LiDAR Point Clouds

Comparison of Filters for Archaeology-Specific Ground Extraction from Airborne LiDAR Point Clouds

Monitoring the understory in eucalyptus plantations using airborne laser scanning

Resource availability and disturbance shape maximum tree height across the Amazon

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